Cad. Saúde Pública vol.22 suppl.


Use of research results in policy decision-making,
formulation, and implementation: a review
of the literature
La utilización de los resultados de la investigación
en el proceso de decisión, formulación y
implementación de políticas: una
revisión de la literatura

Celia Almeida 1
Ernesto Báscolo

1 Escola Nacional de Saúde
Pública Sergio Arouca,
Fundação Oswaldo Cruz,
Rio de Janeiro, Brasil.
2 Instituto de la Salud Juan
Lazarte, Rosario, Argentina.

C. Almeida
Departamento de
Administração e
Planejamento em Saúde,
Escola Nacional de Saúde
Pública Sergio Arouca,
Fundação Oswaldo Cruz.
Rua Leopoldo Bulhões 1480,
Rio de Janeiro, RJ
21041-210, Brasil.




This paper offers a critical review of the theoretical literature on the relationship between the
production of scientific knowledge and its use
in policy formulation and implementation. Extensive academic output, using a diversity of approaches and analytical frameworks, has sought
to systematize knowledge transfer categories
and strategies with a view to improving the application of scientific knowledge. A considerable
part of this thinking addresses the problem from
a more traditional perspective, which (explicitly or implicitly) regards research results as an
“accumulable product”, depicts the decisionmaking process simplistically and linearly, and
thus restricts strategies to the suiting of research
endeavors to needs. Newer approaches place
greater importance on the complexity of policymaking and the knowledge production process, which are integrated into and explained in
particular political and institutional settings.
Although the application of knowledge transfer
ideas to health policy and systems research does
generate some interesting contributions, a long
process of theoretical thinking lies ahead.

Although the debate on the use of research results for policy decision-making and implementation processes is not new and its features have
changed over time, the issue has gained greater
prominence in recent decades following the major processes of world change that increasingly
call for concrete evidence to support or challenge
the innovations that are implemented in a variety of contexts, including health policies and
The background to the debate dates to the
mid-20th century and overlaps the following: (1)
the field of public policy analysis, and thus the
formation of political science as a specific discipline in the social sciences and (2) discussions
of the social sciences approach and methods as
applied to various fields of knowledge, including
health services research.
The literature on the analysis of health and
health systems public policy does not provide a
clear, single definition of either health policy or
health services and systems. However, there is
a clear consensus that what is being analyzed is
public policy, and thus state policy; there is less
agreement (particularly more recently) as to the
scope of such policy and whether health policies
(or at least part of their content) belong to the roll
of social policies.
Importantly, unlike the English-language literature, which distinguishes between “policy”

Health Policy; Policy Making; Use of Scientific
Information for Health Decision Making

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Almeida C, Báscolo E

(policy content, a framework of guidelines for action) and “politics” (the political decision-making process, involving a range of loci and actors),
Latin American literature (in Spanish or Portuguese) uses a single term (política), with various
uses and meanings that encompass both senses.
Public policy analysis emerged, particularly
in the United States, as a science of action, a contribution by experts (analysts) to government
decision-making processes. The central concern
was to direct research in such a way as to be relevant, useful for action. That pragmatic view of
political science came, in turn, as a reaction to a
prevailing formalism 1 and against the abstract
rationalism of Homo economicus 2.
Underlying such an approach was obviously
an ingenuous conception that tended to see a
simplistic relationship between improved understanding of action and better government performance. In the late 1950s and early 60s it was believed that this association between experts (policy analysts) and policymakers would facilitate
solutions to society’s problems. This helped focus
attention on crafting tools to be made available
to politicians and decision-makers, while theoretical considerations were relegated to secondary importance.
This trend was extremely strong in the United States in the 1960s and 70s. According to
some authors it led to the production of “practical” knowledge. This submissive, a-theoretical
view of political science was challenged, thus
sparking interest in other concerns more fundamental to this debate, making it possible to
break out of the vicious circle that threatened
to confine public policy analysis to the “function of a decision-making aid, [placing experts
in the role of ] ‘consultant’ and prince’s helper” 2
(p. 45). This confusion between research and the
operations approach led to a differentiation (and
separation) of functions between scientists and
Paradoxically, however, the resurgence of
theory during the subsequent decades returned
to the same theoretical models that had been
rejected initially, because public policy theories
are not particularly innovative. Whether for or
against, they are rooted in political philosophy
and economic thinking, with the important,
original difference that they address what was
then a little-explored field, i.e., they are based on
empirical research, but do not disregard the implications for action, thus surmounting both the
confusion between “practical usefulness” and
“recipe for government” and the false, radical opposition between theory and practice.
Writing in the context of the process summarized above and concerned with the history and

Cad. Saúde Pública, Rio de Janeiro, 22 Sup:S7-S33, 2006

development of health services research as a field
of inquiry, Greenberg & Choi 3 suggest, based on
Anderson 4, that the development of public policy consensus on a particular issue or set of issues
establishes the basic framework for policy-related social and economic research, within which
research priorities are set.
As Greenberg & Choi 3 (p. 4) emphasize, “two
key words – systematic and instrumental – emerge
from Anderson’s thesis, which is not arguing that
no research or data collection occurs prior to policy
consensus, but rather that large-scale, systematic
collection and analysis efforts only emerge (and
are funded) after the establishment of consensus
on issues to be addressed by particular policies (…)
[and] the resulting research efforts become primarily instrumental in nature. The term ‘instrumental’ refers to work that is oriented to the solution of
specific management program or policy problems
and tends to be constrained by very short time
frames”. Seen in this way, health policy and services research becomes a problem-oriented field
and, thus understood, is instrumental.
It is important to remember that these authors
are discussing the health services research field,
which was developing as part of a much larger
trend towards using applied social science research to improve public decision-making. Many
historians of health policy and health services research argue that this field, as a distinct field of
inquiry, really began in the 1960s 5,6. Before then,
the primary focus of health policy had been to
develop a delivery system that would provide equitable access to care, and the perceived role of
federal government was to channel resources for
that purpose. The 1970s witnessed a shift in the
policy consensus away from access to health care
and expansion of coverage and toward cost containment and “shrinking the system” 3,5,7,8,9,10.
The issue of health sector reform has been on the
agenda of almost all countries ever since, and new
models of health systems and services organization have come into play. New policy instruments
have become necessary, and these have generated great demand for new knowledge about how
to control health systems more effectively.
As part of this process, the health services
research field took on new life in the 1980s, but
received heavy criticism for its apparent failure
to perform as a source of instrumental findings
– the central issue in debate came to be the “use
of research results”. As a result, there is no general
agreement on how to distinguish between applied social science research in health delivery
systems, health services research, and health policy analysis. Such criticism also raises the issue of
emphasis: whether towards theoretical development or problem-solving approaches 3.


In order to help ensure that research would
be “problem-solving oriented” and would focus on desired policy issues, the sponsors and
financers – in many cases mainly the state, i.e.,
the federal government, and international organizations – began to rely more heavily on the
“call for proposals” approach to award grants,
in contrast to the researcher-oriented approach
of the past 3,11. The issue of the diffusion of service innovations gained prominence, as did the
search for evidence for public health and health
policy. Thus, the problems posed by the difficulty
in transferring scientific information or research
results to decision-making have become a subject for academic thinking.
As many authors point out, whether research
results or scientific evidence have contributed
significantly to public policy depends largely on
how one defines public policy and the policy development process. Opposing approaches can be
identified in the recent past.
One view of the policy-making and policyformation processes sees them as sets of explicit,
authoritative decisions by sets of identifiable
public officials. The other view argues that a more
complex, general political process is involved,
strongly influenced by values, opinions, and actions which move decisions in certain directions
in the political, social, and economic systems. In
the first approach, the impact of research results
tends to be evaluated in terms of the direct effects on such decisions; in the second, “research
performance” should be evaluated in terms of
its overall ability to shape debate and action. Accordingly, one should not expect any specific result of any specific study to play a central role in
any specific decision, but should look toward the
nature of the issues being raised and the debate
surrounding theses issues. Greenberg & Choi 3
feel one should at least be able to associate past
and ongoing research with current policy issues
and debates.
In the wake of these discussions and changes
in direction, analysis of the health policy process
has gained prominence, and efforts are under
way to equip and formalize the health sector decision-making process by developing “facilitator”
Generally speaking, the literature warns that
the fields of knowledge production and policy formulation and implementation are very different:
their goals and methods for working and evaluating results are completely different and not
easily interchangeable. Meanwhile, this lack of
clarity makes it difficult to establish strategies
to effectively draw these two activities closer
together on the basis of greater cooperation
and visible, concrete results. In addition, much

of the frustration surrounding attempts to apply research results to policy stems from mistaken expectations as to what such application
means 12, as well as to a lack of any clear perception of what the decision-making process is really
like 13. There is also no single way of viewing that
process, and depending on which analytical perspective is used, the “entry points” for research in
the policy process also shift, as do the variables
that interact in it 14.
Terms such as “informed choice”, “considered
decision”, “rational policy”, “evidence-based policy”, “strategic research”, and “essential national
research” have been used to express the belief
in the need to build a “bridge” between research
and policy. National and international seminars,
congresses, and scientific meetings have focused
on the “research-to-policy” issue. A number of
moves have attempted to facilitate the use of research results in policies, including the preparation of tool kits for defining research priorities,
demand for (and utilization of) health policy and
systems research, and capacity-building (Training Materials and Tools, Alliance for Health Policy
and System Research, http://www.alliance-hpsr.
org); or “political maps” designed to facilitate an
understanding of the decision-making process
15 and mainly involving the national and international financing agencies. Increasingly, such
agencies are requiring that research protocols
state this link explicitly and discuss specific strategies for this purpose. Still, little is known about
where, how, and by whom such a bridge is to be
built 12.
The health field provides abundant examples
of the complex relationship between research
results and policy formulation and of the ways
by which scientific evidence influences specific
causes of disease or individual behavior changes.
Taking prevention as an example (e.g., smoking
and related health damage, or environmental
measures), the evidence is that the accumulated
scientific knowledge on a given issue is not what
determines significant policy or even behavioral
change 16. The interests involved in these issues
are far more varied and extend far beyond the
health sector 3,14.
The purpose of this article is to offer a literature review on this subject, based on selected authors, and to discuss their arguments and some
of the main theoretical approaches to explain or
back the relationship between the production
of scientific knowledge and its use in policy formulation and implementation. The first section
presents several analytical models designed to
explain these relationships. The second reviews
the issue of the use of research results and policy-making. The third analyzes the literature on

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Almeida C, Báscolo E

the interaction between researchers and policymakers. The fourth reviews issues related to
the spread of knowledge, knowledge transfer,
and evidence base in health policy and practice.
The initial hypothesis is that there is an excessive formalization of instruments and pragmatic
simplification in the proposals designed to draw
the two fields (research and policy) closer, while
the importance of formulating and developing
analytical and explanatory frameworks that perhaps offer more promise in this process is underestimated.

Some explanatory models for use
of research in policy
The term “knowledge transfer” is increasingly
used to describe a series of activities contained
in the process of generating knowledge based
on user needs, disseminating it, building capacity for its uptake by decision-makers, and finally
tracking its application in specific contexts. While
there is increasing interest in knowledge transfer for health policy and practice, there is still no
dominant explanatory model to guide efforts in
this area, and there is little empirical research on
what has worked in specific contexts.
Weiss 17 is cited in the literature as having
pioneered the identification and description of
seven models to illustrate how research is used in
policy formulation or how it functions as a guide
for the decision-making process. From those
models, authors are defining analytical categories that enable this knowledge to be extended.
Trostle et al. 12 summarize these models in
three basic approaches: (1) the rational approach
includes the models that Weiss calls “knowledgedriven” and “problem-solving”, representing the
conventional manner of thinking about this relationship: the policy process is inherently rational,
with research results being used when they exist
and decision-makers calling for research when it
is needed; (2) the strategic approach groups the
models Weiss calls “political” and “tactical” and
views research as a kind of ammunition in support or critical of certain positions, prompting or
delaying policy action; and (3) the enlightenment
or diffusion approach, comprising Weiss’ three
remaining models – “interactive”, “enlightenment”, and “intellectual enterprise” – and stressing that both the research and decision-making
processes take place in parallel with a number
of other social processes and thus play several
different roles.
The knowledge-driven model assumes that
basic research leads to applied research, to development, and finally to application of the re-

Cad. Saúde Pública, Rio de Janeiro, 22 Sup:S7-S33, 2006

sults, and the problem-solving model starts with
a problem that needs solving, in turn requiring
research, the results of which lead to action being
taken. The political and tactical models connect
directly to executive action; and the last three
– interactive, enlightenment, and intellectual enterprise – relate to the production of scientific
knowledge in a given line of research, fostering a
build-up of knowledge that (it is believed) gradually informs action 13.
In the late 1980s, the concept of use expanded to encompass at least three different types of
meaning: (1) instrumental, as an input to decision-making; (2) conceptual, contributing to
improved understanding of the subject matter,
the related problems, or the political interventions under study; and (3) strategic, serving to
persuade other actors or as a means to attain certain aims 18.
With regard to evaluation of study results,
Kirkhart 19 criticized the traditional concept of
use as being unidirectional, episodic, intended,
and instrumental. It failed to adequately describe
types of impact deriving from sources other than
the results of evaluation, or unintended results or
gradual, incremental impact over time. Kirkhart
addressed issues such as the ways by which the
results of an evaluation study are used, including
an examination of the ways (how and to what extent) the evaluator participates, affects, supports,
and proposes mechanisms that foster behavior
changes in people and systems. This places new
importance on the impact of evaluation itself,
rather than on any immediate use of its output 20.
From this perspective, it is supposed to be easier
to measure the extent of changes in a program
or the views of strategic actors than in the use of
study results.
In a similar approach, Rich 21 characterizes
the use of research results in the following stages,
viewed from a process perspective: information
pick-up, processing, and application.
Kirkhart thus proposes the development of an
integrated theory of influence, enabling the impact of research or evaluation to be assessed, by replacing the category “use” (with its more restricted
meaning) with “influence”, defined as the “capacity or power of persons or things to produce effects
on others by intangible or indirect means” 19 (p. 7).
The integrated theory of influence rests on
three dimensions: source, intention, and timing.
Source relates to the initial cause of a process of
change. Sources can arise either in the evaluation process (process-based) or the results (results-based). The former are oriented towards
increasing understanding among the actors,
changing their sense of the values and developing new relationships, dialogues, and networks.


The categories used are: (i) cognitive changes in
understandings stimulated by the discussion, reflection, and problem analysis in an evaluation
study; (ii) affective changes in the individual and
collective feelings of worth and value resulting
from involvement in a study; and (iii) political
changes resulting from the role of evaluation in
creating new dialogues, drawing attention to
social problems, or influencing power relationships. Evaluation of results is seen in terms of the
more conventional categories of instrumental,
conceptual, symbolic, and strategic influence.
A second dimension of influence identified
by Kirkhart 19 (p. 11) is intention, defined as “the
extent to which evaluation influence is purposefully directed, consciously recognized and planfully anticipated” and characterized by the type, target, and sources of influence (people, processes,
and findings). Other complementary features are
dimension (intended/unintended), explicitness
(manifest/latent), orientation (results-oriented/
process-oriented), and direction (positive/negative). Lastly, influence is seen in terms of three
categories of temporal dimension: immediate
(during the study), end-of-cycle, and long-term.
Patton 22 identifies a typology of use that
stresses processes rather than products: (1) enhancing shared understandings, especially about
results; (2) supporting and reinforcing the program through intervention-oriented evaluation;
(3) increasing participants’ engagement, sense of
ownership, and self-determination; and (4) program or organizational development.
Meanwhile, Forss et al. 23 expand on the previous proposal to identify five types of process-related use: learning to learn; developing networks;
creating shared understanding; strengthening
the project; and boosting morale.
Despite the extensive literature (the majority of the studies have not been cited here), the
state-of-the-art on the most effective and efficient knowledge transfer strategies is still in its

Use of research results and
policy-making in health
The authors’ thinking and models are useful for
understanding the various ways by which research results are used in policy-making. However, Walt & Gilson 13 emphasize that the underlying assumption of many is that both research
and policy-making are logical, rational processes
where researchers ask the right questions, plan
and conduct their studies rigorously, and circulate their results appropriately, and that decision-makers read research reports, understand

the results and their implications, and act to
correct their course in the direction indicated.
Even admitting to a specific rationality in each
of these processes, the real world is not so linear: new knowledge and information do in fact
penetrate the policy sphere and become part of
decision-makers’ argumentation and thinking,
but in a much more diffuse way that depends on
the accumulation of scientific information on a
given issue, the political environment, and the
conjuncture, among numerous other variables.
The search to find (and accumulate) evidence
thus becomes the other important part of this
In order to capture this dynamic, Walt & Gilson 13 suggested the use of other analytical categories to understand the influence of research
on specific concrete cases, namely policy content, social actors, decision-making process, and
These are basic political science categories.
The formulation, implementation, and evaluation of social policies are heavily guided by the
values and concepts of social realities shared by
the leading actors in the various process levels,
or by bureaucratic elites. These values and concepts provide the “terms of the debate” on policies, delimiting and circumscribing the policy
agenda at any given moment 24. Meanwhile, the
political, economic, and institutional context of
the decision-making process shapes the range
of available options and affects decision-makers’
choices 25, i.e., “the ways in which the evidence is
used in the policy process are largely determined
by beliefs and values of policymakers, as well as
by considerations of timing, economics, costs, and
politics” 27 (p. 601). Besides, the policy formulation process is completely different from the
implementation process, so that a proposal for
change rarely retains its original characteristics
when implemented, because it alters the status
quo and mobilizes actors to defend their interests. Overall, the central category that emerges
from such discussions is power, with its innumerable facets and dimensions.
Brown 14 (p. 20) asserts that the numerous
generalizations on the role of health systems and
services research in the political process are not
particularly useful, because as a power resource,
knowledge plays innumerable roles, which
change with place, time, and circumstances. Each
concrete case also involves different explanatory
variables for policy change, and each variable implies that the research has played a specific role.
Some variables are particularly important, as
Brown points out on the basis of case studies in
the United States. Trostle et al. 12 find the same in
their Mexican case studies on the same subject.

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There is a certain consensus among authors
concerning various barriers that hinder or prevent research from being used in the decisionmaking process. These include:
a) Ideological problems that constrain political
rhetoric and the formulation of reform agendas,
in addition to a lack of political “will” or an inability to formulate and implement more integrated,
interactive policies;
b) Historical separation between researchers,
policymakers, service providers, administrators,
managers, etc., allied to a mutual intellectual disdain 12;
c) “Uncertainty” caused by scientific divergences among researchers on any given problem
(conceptual confusion, methodological problems); by the very changes that scientific and technological progress foster in explanations of any
given phenomenon, meaning that the scientific
“truths” of today are challenged tomorrow; and
because the information is fragmented, with different definitions of the important problems;
d) Different conceptions of risk at the individual or collective level, and in the same sector or
among various sectors, particularly in multi-sector actions (e.g. environmental control, tobacco
use, alcohol, diet, and nutrition);
e) Media interference, which can both confuse
the issue by publicizing results inappropriately
and exploit divergences rather than clarifying
f) Marketing and circulation of research: researchers using impenetrable language; inappropriate means restricted to “peer” forums and publications; and
g) Research process timeframes out of step with
those of the decision-making process.
Trostle et al. 12, analyzing the Mexican case
studies, identify both barriers and factors that
promote and facilitate the use of research results in policy in each of the analytical categories
suggested by Walt & Gilson, which are generally
specific to each policy area under consideration.
However, little headway has been made on proposals to surmount these barriers; the question
is whether simply surmounting them will solve
the impasses or whether this approach (although
necessary) is really sufficient to promote greater
use of research in policy formulation and implementation.
Brown 14 argues that some variables are fundamental, although they should not be considered absolute. In addition, the degree to which
research actually influences policy varies inversely with the complexity of the issue under
study. The first health services research activity
that he identifies with an important influence
on policy formulation and implementation (and

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which is not exactly research, but relates to it) is
documentation: the gathering, cataloguing, and
correlating of facts depicting the state of affairs
that policy-makers wish to change. In addition,
compiling statistical data allows establishing
temporal and spatial correlations.
However, Brown cautions that quantitative
and qualitative databases and statistical indicators cannot be considered research results per
se, but are the raw material on which research
is shaped and without which it cannot be conducted. He also emphasizes that “documentation
is not always a step toward action; sometimes it
stultifies it” 14 (p. 28). When the right predisposition or political and material conditions exist,
information can become a powerful weapon to
spur the shift from political rhetoric to concrete
action. However, information alone cannot create such a predisposition. Likewise, Bardach 27
states that policy analysis theory proposes that
evidence is information that affects existing
beliefs by important persons about significant
features of the problem under study and how it
might be solved or mitigated.
A second role of health service research in
policy design, according to Brown 14, is analytical, i.e. demonstrating what works or does not,
and explaining why. In a conflictive reform context, research that raises doubts about the omnipresent list of alternatives for government intervention can prompt policy-makers to take action.
Yet it also is a two-edged sword, since it can call
attention to aspects unforeseen by policymakers
and thus discredit both the policy as formulated
and the proposed alternatives.
Bowen & Zwi 26 (p. 601) also argue that “the
way in which research evidence is combined with
other forms of information is key to understanding the meaning and use of evidence in policy development and practice. (...) A major challenge
to contextualizing evidence for policymaking is
recognition that a broad information base is required [and] (…) considering the evidence within
the context in which it will be used is critical for
effective policymaking and practice”.
A final role that Brown highlights for health
systems and services research is prescription. The
political force of empirical evaluation and analytical constructs resides in the “scientific” character they lend to reform proposals, reinforcing
decision-makers’ prior positions.
Research can thus play a variety of roles in
policy. The task of prescription differs greatly
from those of documentation and analysis: demonstrating how and why the system functions is
itself a contribution to the production of knowledge, which is the essence of research activity,
but on its own that contribution will not “teach”


decision-makers how to change the system. On
the other hand, more narrowly focused studies,
directed exclusively to problem-solving, have no
broader implications and do not contribute to
the build-up of knowledge achieved by pursuing
a line of research that lasts over time.
Prescription requires understanding not just
how and why actors and institutions behave as
they do under given conditions, but also (and
more importantly) how such behavior can be altered under new conditions; and here not even
the most complete documentation or analysis is
enough to ensure any result. In addition, in order
to “prescribe” solutions, researchers would have
to shed their academic guise and explore avenues not entirely authorized by their theoretical
and methodological frameworks, thus running
the risk of being discredited by actual developments. Seen thus, health systems and services
research has been very erratic as a prescriptive
guide and, in the endeavor, has tended to deviate from the field of research and to confuse it
with others, such as technocratic and planning
activities. In practice, however, these fields are
very different and operate with distinct conceptual universes.
In summary, Brown 14 regards research as
most valuable to policy in supporting the documentation that describes the system; most erratic in analyzing how policy functions and
explaining what works, and how and why; and
considerably limited in its prescriptive capacity.
Thus, the potential contribution of research to
the decision-making process has less to do with
offering definitive solutions to the problematic
issues in debate and more with improving the
quality of the terms of the debate. Thus, the ability to change the nature of public debate on a given issue is an important form of power, because
bringing ideas, proposals, and interests into
confrontation is an important force in changing
the balance of power among the various contesting groups. Other authors, like Weiss 17 and Majone 28, reinforce this argument.
The contradiction here is that as the research
field becomes more developed and promising,
the range of results, explanations, arguments,
and recommendations tends to expand, and the
field may thus appear more “chaotic” to decisionmakers. In other words, an active, highly-skilled
scientific community in the health systems and
services research field, closely attuned to institutional niches in the state apparatus and civil
society and with a secure place in the decisionmaking arena (such as the “policy networks” 29,30
or the “epistemic communities” 31,32) is certain
to foster better debate, but not necessarily better
policy results.

Also distant from the “rational” approach and
closer to Brown and Walt, some authors recognize an “incremental” dimension to the use of
knowledge 26,33,34, placing new importance on
the complexity of the decision-making process;
this dimension identifies conditioning factors
complementary to scientific knowledge, such as
interests, values, established institutional positions, and personal ambitions. This view includes
a political and institutional approach to the decision-making process, where identifying and
characterizing the actors and interrelations is a
key dimension to understanding the process and
the use of research results in a framework of political negotiation, rather than restricted to criteria sustained by scientific evidence.

Interaction between researchers and
decision-makers as an explanatory
dimension conditioning the use
of research results
Interrelations between researchers and decisionmakers have been considered a prime factor in
analyzing knowledge transfer processes. Analysis
of the weaves (or models) of interrelations between researchers and decision-makers is relevant
when one realizes that the use of scientific knowledge depends largely on certain characteristics
of the actors (researchers’ behavior and de-cision-makers’ receptiveness). Various authors have examined and promoted different ways of improving interrelations between researchers and
decision-makers, such as collaborative or “allied
research” 35, or constructivist approaches to evaluative research 36, including strategies to improve
the knowledge output for decision-making.
This approach fosters a political and institutional analysis of relations between actors and organizations in the interconnections between research and policy formulation and implementation processes as a conditioning (or independent)
variable in the use of knowledge or its impact on
decision-making processes (dependent variable). Kothari et al. 37 evaluate the implications of
different interrelations between researchers and
decision-makers for the use of research results
in health policies and programs. Their conceptual framework for such interactions is based on
Rich 21, viewing possible opportunities for contact at the following research stages: (i) defining
the research questions; (ii) conducting the research, and the research findings; (iii) circulating
results; and (iv) research utilization, defined as
the ways by which research findings influence
decision-makers. As already mentioned, use is
characterized by dimensions in which several

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stages play out from a process perspective, summarized as receiving and reading; information
processing; and application.
Viewed in a less linear light, interaction could
be defined as a number of “disordered interactions” that take place between researchers and
users, more than a sequence starting with the
needs of researchers or decision-makers.
Lomas 38 has built on this literature and used
the term “push and pull” to describe specific potential actions to promote knowledge transfer.
Push strategies involve transforming the message
according to the needs of specific audiences. This
represents a departure from “one-size-fits-all”
dissemination strategies. Pull strategies include
efforts to build capacity at the user end, such as
workshops to explain how to access information
and evaluate its scientific rigor.
Meanwhile, Lomas 39, Lavis et al. 40, and Landry
et al. 41 draw on the literature of action science and
participatory research to suggest that these contact
situations or interfaces must be leveraged from
the beginning of the research process to promote
activities that create “linkages”. Such activities
include providing opportunities for researchers
and users to jointly define the research question,
maintain contact during the research process,
and (following completion) discuss findings and
the potential implications for policy and practice.
Landry et al. 42 analyzed research use as the
dependent variable and its association with a
wide range of independent determinants, including various knowledge transfer activities. Research use was measured on a scale of one to six
using Knott & Wildavsky’s 43 self-reported index,
as follows:
1) Reception: received research pertinent to
one’s work;
2) Cognition: read and understood it;
3) Discussion: discussed the research in meetings;
4) Reference: cited the research in reports/presentations;
5) Effort: made an effort to favor the use of research; and
6) Influence: the research influenced decisions.
In their study of 833 Canadian policy-makers,
Landry et al. 42 grouped independent variables
by conceptual paradigm and implicit assumptions about factors that increase research use.
They found that scholarly research was as likely
to be used as applied research, and that highly
theoretical qualitative research was slightly less
likely to be used than quantitative studies. Their
conclusions can be summarized as follows:
• Factors deriving from the “two-communities”
approach, such as whether there had been specific efforts to tailor research for users (push) and
to build capacity among decision-makers to use

Cad. Saúde Pública, Rio de Janeiro, 22 Sup:S7-S33, 2006

research (pull), were found to be highly related to
• Similarly, the “linkages” approach, which
posits that more interaction with researchers
throughout the research cycle improves use, proved to be a significant determinant of use;
• “Engineering solutions”, cited by those who
believe research can “fix” policy problems, propose that the type of research (applied versus
scholarly or qualitative versus quantitative) is the
most important determinant of use;
• “Organizational factors” like structure, size,
culture, and policy domain are often posited as
important determinants, but were not found to
be associated with research use;
• Among the “individual factors” often assigned importance, like educational level and position within an institution, education was indeed
found to be associated with higher levels of research use, although position within an organization was not.
Looking at the knowledge production and decision-making processes suggests several points
where contact between these two dimensions
and logics could be useful. The identification
and analysis of these points of contact or interfaces charts another process: the interrelations
between researchers and decision-makers.
Trostle et al. 12 offer a graphic representation
of the dynamic relationship between research and
policy formulation, highlighting that although
the processes are usually independent of each
other, there may be connections between them.
They call these contacts “moments of opportunity”, since the actors in one process learn from
or contribute to those in the other. They also emphasize that the main challenge for applying research results to policy is to learn to create or recognize such moments of opportunity, and then to
act effectively to take advantage of them. Starting
with the left side of a conceptual figure and moving counter-clockwise, the research process includes the stages of idea generation, design, data
gathering, analysis, and application (an interrelationship represented by arrows). Following the
arrows, the research results can lead to new ideas
and research projects, or may also be applied.
The policy process is similarly represented,
starting on the left side of the conceptual figure
and moving clockwise. When the needs or problems that arise can be addressed on the basis of
specific policies, there is an endeavor to gather
information on them from a variety of sources. Interest groups may lobby at various moments and
thereby influence definition of priorities among
the needs, decisions, or policies. As in the previous process, some arrows return to the information-gathering stage, before policy is designed.


Some decisions generate a search for additional
information and further negotiations, while others produce policies. New policies can also lead to
new interest groups and new political challenges.
Other authors 44 formulate concepts similar to
the “moments of opportunity”, containing the idea
that knowledge can be useful in generating change only when a “window of opportunity” appears.
It is important that analysis examines the actors in the process and evaluates the sources of
information they trust, the type of information
that interests them, how they evaluate information, what motivates them to make decisions,
and the actors with whom they interact, compete, and form alliances.
Trostle et al. 12 and Bronfman et al. 43 also
offer a graphic representation of relations between actors and context. In their figure, two
larger intersecting circles represent civil society
and the state. Other smaller circles represent the
interest groups’ real or potential impact on policies. Researchers are one such group. Also shown
graphically are the mutual influences between
interest groups and decision-makers. Public policies (the focus of their study) are formulated by
public decision-makers and thus stand at the intersection between state and civil society. Actors
are located in one sphere or another, or at their
Other studies propose a variant on stakeholder analysis, featuring researchers as a group with
the ability to intervene in the decision-making
process 46 and in the policy formulation process
directly or through other key stakeholders over
whom they have influence. This interpretation
sees the decision-making process as susceptible
to influence not only from the knowledge generated by research, but also from the research
process itself. This notion allows analyzing the
influence of the knowledge produced separately
from the influence of the process by which such
knowledge is produced.
Similarly, the position to be taken towards
the problem at hand cannot be interpreted separately from the context and stakeholder analysis.
In some situations, objective variables predominate and an instrumental approach may be sufficient. In others, subjective variables predominate, making it possible to opt for a conceptual
or symbolic approach.

Diffusion, knowledge transfer,
and evidence base in health
policy and practice
Many proponents of research use in health care
have drawn on the theory of diffusion of innova-

tion 47. As Bowen & Zwi 26 (p. 600) also point out,
“the contemporary public health effort sees much
debate about the concepts of ‘evidence’ and ‘the
evidence base’, and the usefulness and relevance
of such terms to both policy-making and practice”.
A key challenge would be to better contextualize
evidence for more effective policy-making and
Greenhalgh et al. 48 conducted a systematic
review (commissioned by the UK Department of
Health) of the diffusion of service innovations.
Drawing on Rogers’ overview 47 and other empirical work, they formulated a unifying conceptual
model that, instead of serving as a prescriptive
formula, intended to be mainly a mnemonic aid
for considering the different aspects of a complex
situation and their many interactions. These authors define “‘innovation’ in service delivery and
organizations as a novel set of behaviors, routines,
and ways of working that are directed at improving health outcomes, administrative efficiency,
cost effectiveness, or users’ experience and that
are implemented by planned and coordinated
actions”. The authors distinguish between “‘diffusion’ (passive spread), ‘dissemination’ (active
and planned efforts to persuade target groups to
adopt an innovation), ‘implementation’ (active
and planned efforts to mainstream an innovation within an organization), and ‘sustainability’
(making an innovation routine until it reaches
obsolescence)” 48 (p. 582).
For the purposes of this study, we highlight
some issues emphasized by the authors. Their
view is that “the various influences that help
spread the innovation can be thought of as lying on
a continuum”. In pure diffusion the spread of innovation is unplanned, informal, decentralized,
and largely horizontal or peer-mediated, while
active dissemination is planned, formal, often
centralized, and likely to occur more through vertical hierarchies. Whereas mass media and other
impersonal channels may create awareness of
an innovation, interpersonal influence through
social networks is the dominant mechanism for
diffusion. “The adoption of innovation by individuals is powerfully influenced by the structure
and quality of their social networks, and different
social networks also have different uses for different types of influence” 48 (p. 601-2).
According to their review, the literature on
diffusion of innovation in health care organizations is vast and complex and contains many
well-described themes, such as the useful list
of attributes of innovation that predict (but do
not guarantee) successful adoption, and the importance of social influence and the networks
through which it operates. They also exposed the
lack of empirical evidence for the widely cited

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Almeida C, Báscolo E

“adopters’ traits”, the limited ability to generalize
from the empirical work, and the near-absence
of studies focusing primarily on the sustainability of complex service innovations. Finally, they
emphasize the multiple and often unpredictable
interactions arising in particular contexts and
settings, which determine the success or failure
of a dissemination initiative, and “clear knowledge gaps” where further research on diffusion of
innovation in service organizations should focus.
One of the study’s most important outputs, resulting from their analysis of the literature, was a
parsimonious, evidence-based model for considering innovation diffusion in this area 48.
Based on a thorough literature review, Bowen
& Zwi 26 (p. 600) propose an “evidence-informed
policy and practice pathway to help researchers
and policy actors navigate the use of evidence”.
The pathway involves three active stages of
progression, influenced by the policy context:
sourcing, using, and implementing the evidence.
It also involves decision-making factors and a process they call “adopt, adapt, and act” 26 (p. 600).
The authors argue that the term evidencebased policy is used largely for one type of evidence (research) – using the term evidence-influenced or evidence-informed would reflect the
need to be context-sensitive and concerned with
everyday circumstances – and that the types of
evidence that inform the policy process can be
grouped as research, knowledge/information,
ideas/interests, politics, and economics.
In their attempt to construct a more comprehensive framework to understand the use of
evidence for policy, Bowen & Zwi 26 (p. 602) define the categories of “relative advantage, compatibility with values and past experience, cost
and flexibility, trialability, and reversibility, policy
environment” and others, besides conducting
a critical review of the literature on knowledge
transfer, diffusion, and innovation.
Meanwhile, they emphasize that “it is difficult
for evidence to remain intact through the process
given the policy context, decision-making factors,
and the need to adapt”, indicating that “evidence
interacts with ‘context’ before it is fully adopted in
policy and practice, and/or that different types of
evidence are useful at different times in the policy
process”. Therefore, “effective knowledge transfer
is not a ‘one off ’ event, rather it is a powerful and
continuous process in which knowledge accumulates and influences thinking over time”. Thus,
“the ability to sustain this process and a focus
on human interaction is essential. Differences in
conceptual understanding, scientific uncertainty,
timing, and confusion influence the response to
evidence”. In summary, “understanding knowledge utilization in policymaking requires an un-

Cad. Saúde Pública, Rio de Janeiro, 22 Sup:S7-S33, 2006

derstanding of what drives policy...” and “determining capacity to act on evidence is a neglected
area of policy analysis and research efforts to
date” 26 (p. 603-4). In other words, understanding
how evidenc

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